Find differences between R objects
The goal of waldo is to find and concisely describe the difference
between a pair of R objects, with the primary goal of making it easier
to figure out what’s gone wrong in your unit tests.
waldo::compare()
is inspired by all.equal()
, but takes additional
care to generate actionable insights by:
You can install the released version of waldo from
CRAN with:
install.packages("waldo")
library(waldo)
When comparing atomic vectors, compare()
produces diffs (thanks to
diffobj) that highlight additions,
deletions, and changes, along with a little context:
Deletion
compare(c("a", "b", "c"), c("a", "b"))
Addition
compare(c("a", "b"), c("a", "b", "c"))
Change
compare(c("a", "b", "c"), c("a", "B", "c"))
Long vectors with short differences only show local context around
changes, not everything that’s the same.
compare(c("X", letters), c(letters, "X"))
Depending on the relative size of the differences and the width of your
console you’ll get one of three displays:
The default display is to show the vectors one atop the other:
compare(letters[1:5], letters[1:6])
If there’s not enough room for that, the two vectors are shown
side-by-side:
options(width = 20)
compare(letters[1:5], letters[1:6])
And if there’s still not enough room for side-by-side, the each
element is given its own line:
options(width = 10)
compare(letters[1:5], letters[1:6])
When comparing more complex objects, waldo creates an executable code
path telling you where the differences lie:
Unnamed lists are compared by position:
compare(list(factor("x")), list(1L))
Named lists, including data frames, are compared by name. For example,
note that the following comparison reports a difference in the class
and names, but not the values of the columns.
df1 <- data.frame(x = 1:3, y = 3:1)
df2 <- tibble::tibble(rev(df1))
compare(df1, df2)
Recursion can be arbitrarily deep:
x <- list(a = list(b = list(c = list(structure(1, e = 1)))))
y <- list(a = list(b = list(c = list(structure(1, e = "a")))))
compare(x, y)